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PubMedDate not supplied

Contraceptive use in Matlab, Bangladesh: the role of gender preference.

Research in several Asian societies has suggested that sons are generally preferred over daughters. The implications of gender preferences for actual fertility behavior have not been adequately investigated, however. This analysis examines the effect of the sex composition of surviving children on the acceptance and discontinuation of contraception in a sample of 3,145 women in Matlab, Bangladesh, who were observed for 60 months. Hazards regression analyses are employed in the analysis. Strong and highly significant effects of gender preference on contraceptive use are observed. The preference is not monotonically son-biased but is moderated toward a balanced composition, because parents desire to have several sons and at least one daughter. These findings suggest that gender preferences, particularly a preference for sons, represent a significant barrier to fertility regulation in rural Bangladesh.

Bangladesh↗
PubMed2001

A new algorithm for autoregression moving average model parameter estimation using group method of data handling.

A new algorithm for autoregresive moving average (ARMA) parameter estimation is introduced. The algorithm is based on the group method of data handling (GMDH) first introduced by the Russian cyberneticist, A. G. Ivakhnenko, for solving high-order regression polynomials. The GMDH is heuristic in nature and self-organizes into a model of optimal complexity without any a priori knowledge about the system's inner workings. We modified the GMDH algorithm to solve for ARMA model parameters. Computer simulations have been performed to examine the efficacy of the GMDH and comparison of the GMDH is made to one of the most accurate and one of the most widely used algorithms, the fast orthogonal search (FOS) and the least-squares methods, respectively. The results show that in some cases with noise contamination and incorrect model order assumptions, the GMDH performs better than either the FOS or the least-squares methods in providing only the parameters that are associated with the true model terms.

Algorithms↗
PubMed1990

Is there an optimal degree of acid suppression for healing of duodenal ulcers? A model of the relationship between ulcer healing and acid suppression.

The optimal degree and duration of suppression of gastric acidity required for the healing of peptic ulcers has never been established. Although very potent inhibitors of acid secretion are now available, the need for this degree of suppression has not been shown, and there is a possibility of adverse effects because of pronounced acid inhibition. Therefore, a model has been constructed that defines the relationship between duodenal ulcer healing and antisecretory therapy. Acid suppression data were obtained directly from investigators as raw data from 24-hour studies of acid secretion. Twenty-one experiments from seven investigators provided 490 24-hour studies using 19 different treatment regimens. Healing data were collected from a metaanalysis of published clinical trials of duodenal ulcer healing. A total of 144 published trials in 14,208 patients provided healing data at several endoscopic endpoints for the 19 drug regimens for which acidity data were provided. Weighted least-squares polynomial regression analysis was used to define those parameters of antisecretory therapy that contributed most to duodenal ulcer healing and to define the shape of the response surface. A highly significant correlation (r = 0.9814) was found between healing and the degree of acid suppression, the duration of acid suppression, and the length of therapy. The shape of the contour expression this relationship shows that healing increases as the duration of suppression increases and as gastric pH increases. However, suppression that increased pH beyond 3.0 was not found to increase ulcer healing further. It is concluded that a longer duration of antisecretory effect and/or a longer duration of therapy are of greater importance than potency for duodenal ulcer healing.

Antacids↗
PubMedDate not supplied

Usefulness of measures of Svo2, Spo2, vital signs, and derived dual oximetry parameters as indicators of arterial blood gas variables during weaning of cardiac surgery patients from mechanical ventilation.

OBJECTIVES: To determine whether combined use of the parameters of mixed venous oxygen saturation, arterial oxygen saturation obtained by pulse oximetry (Spo2), and vital signs correlated with arterial blood gas variables (ABGs) better than each individual variable during weaning of postoperative cardiac surgery patients from mechanical ventilation; and to evaluate the relationship of derived parameters: oxygen extraction index and ventilation/perfusion index (VQI), and ABGs. DESIGN: Secondary analysis of previous correlational study. SETTING: The cardiac care unit in a large medical center in central Florida. PATIENTS: Thirty postoperative coronary artery bypass graft patients being weaned from mechanical ventilation. METHODS: After a change in ventilator settings during systematic weaning towards extubation, measurements of variables were taken during a 30-minute period. At 30 minutes, an ABG was drawn for comparison. Data were collected after two ventilator changes. A total of 57 data sets were used for analysis. RESULTS: By use of multiple regression analyses, statistically significant (p < 0.01) independent variables predicting pH and partial pressure of carbon dioxide were Spo2 and respiratory rate. The independent variable contributing to the model versus partial pressure of oxygen was Spo2. The oxygen extraction index did not correlate with ABGs; however, the VQI correlated significantly with all ABG variables except bicarbonate. CONCLUSIONS: The use of multiple parameters was no more useful in predicting ABGs than individual variables of Spo2 and respiratory rate. The derived VQI parameter correlated with ABGs. The use of VQI in conjunction with Spo2 and respiratory rate may assist in patient monitoring during weaning and reduce the number of ABGs needed.

Adult↗
PubMed2006

State-level adjusted ESRD incident rates: use of observed vs model-predicted category-specific rates.

Because of differences in case-mix across states, state-level case-mix-adjusted end-stage renal disease (ESRD) incident rates are reported in each United States Renal Data System Annual Data Report to make the across-state comparisons valid. The adjusted rates were estimated by the direct adjustment method, a widely used method for adjusted event rate calculation, based on observed category-specific ESRD incident rates in each state (called the observation-based method). However, when some adjusting categories in a state are small, the adjusted rate and the standard error for this state as estimated by this method may be inaccurate. This report proposes a model-based method that can overcome the disadvantages of the observation-based method and can be extended to continuous adjusting variables. National ESRD incident data and national population data from 1990 to 1999 were used. State-level adjusted ESRD incident rates were estimated by both the observation- and the model-based methods. For the model-based method, a Poisson regression model was used to estimate category-specific ESRD incident rates. For large-population states, both observation- and model-based methods produced similar estimates for adjusted ESRD incident rates. For small-population states, however, the observation-based method produced year-to-year estimates of adjusted ESRD incident rates that varied considerably and also had very large standard errors. In contrast, the model-based method produced stable estimates. The model-based method can overcome the disadvantages of the observation-based method for estimating state-level adjusted ESRD incident rates, especially for small states.

Age Distribution↗
PubMed2004

[Theory, method and application of method R on estimation of (co)variance components].

Theory, method and application of Method R on estimation of (co)variance components were reviewed in order to make the method be reasonably used. Estimation requires R values,which are regressions of predicted random effects that are calculated using complete dataset on predicted random effects that are calculated using random subsets of the same data. By using multivariate iteration algorithm based on a transformation matrix,and combining with the preconditioned conjugate gradient to solve the mixed model equations, the computation efficiency of Method R is much improved. Method R is computationally inexpensive,and the sampling errors and approximate credible intervals of estimates can be obtained. Disadvantages of Method R include a larger sampling variance than other methods for the same data,and biased estimates in small datasets. As an alternative method, Method R can be used in larger datasets. It is necessary to study its theoretical properties and broaden its application range further.

Algorithms↗
PubMed1996

A new model to predict final height in constitutionally tall children.

In order to develop new height prediction models for children with constitutionally tall stature, 55 such boys and 88 girls were recalled for measurement of adult final height (FH). Data on height (H), age (CA), and target height (TH) were collected from the hospital charts and radiographs of the left hand and wrist were retrieved and used for bone age (BA) determination [BA according to the methods of Greulich and Pyle (BAGP) and Tanner and Whitehouse (BARUS)]. Standard multiple regression techniques were used to develop prediction equations for FH. In addition to test the validity of the new equations, FH was measured in a second group of constitutionally tall children (n = 32) and compared with the predicted FH according to our models. In addition, a comparison was made with other prediction methods. Mean (SD) FH was 196.0 (4.9) cm in boys and 180.5 (3.8) cm in girls. The ultimate regression equation was FH (cm) = 216.07 + 0.75 x H + 0.25 x TH -11.09 BAGP + 0.74 x (CA x BAGP) for boys and FH = 161.42 + 0.73 x H + 0.15 x TH - 8.41 x CA -8.83 x BARUS -2.45 x M + 0.55 x (CA x BARUS) for girls. The models showed satisfying accuracy: the mean (SD) errors were -1.4(3.2) cm for boys and -0.5(3.1) cm for girls with corresponding mean (SD) absolute errors of 2.7 (2.2) cm and 2.0 (2.4) cm, respectively. Compared with the current prediction methods, the new models were quite promising. Their clinical validity has to be ascertained in larger groups of tall children.

Adult↗
PubMed2003

Application of survival analysis to carious lesion transitions in intervention trials.

OBJECTIVE: To demonstrate the usefulness of a survival-time regression model for the analysis of data from two 3-year trials of the caries-preventive effect of sugar-substituted chewing gums and fluoride toothpaste, carried out among 892 Lithuanian children. METHODS: A caries onset was defined as a transition from sound to carious and a caries recovery was defined as a transition from carious to sound. The time at risk for each type of transition was calculated. Using an exponential survival-time regression model, the hazard ratios for the covariates experimental group (control, sugar substitute, fluoride), age, gender, surface type and posteruptive surface age was estimated. This analysis was repeated using two alternative definitions of the caries transitions. RESULTS: The analyses confirmed that caries rates are higher in occlusal surfaces, and that posteruptive surface age influences caries rates. Moreover, it also confirmed that fluoride affects the outcome of ongoing caries activity more than the initiation of caries. CONCLUSIONS: Survival-time analysis of caries transitions allows for the extraction of much more information from caries trials than does the traditional DMF-based analysis, and traditional DMF incremental values may easily be derived from the models.

Age Factors↗
PubMed2006

How to use difference plots in quantitative method comparison studies.

Quantitative method comparison studies are fundamental to clinical biochemistry. The interpretation of quantitative method comparison studies relied heavily on correlation and regression methods until Bland and Altman first described the concept of absolute difference plots. Since then, many clinical biochemistry journals advocate the use of difference plots; however, there is a lot of ignorance about the validity as well as the pros and cons of the various difference plots. The most important issue in quantitative method comparisons studies is to determine limits of agreement that are valid across the whole range of values in the study so that correct data interpretation and conclusions occur. This article discusses validity as well as the pros and cons of difference plots and provides means to determine limits of agreement that are valid across the whole range of values in method comparison studies. Accordingly, correct data interpretation will be more likely and better conclusions should be arrived as a result.

Biomedical Research↗
PubMed2005

Anxiety, depression and quality of life in colorectal cancer patients.

BACKGROUND: Few studies have examined psychological distress and its relationship with quality of life (QL) dimensions in colorectal cancer patients. METHODS: One hundred and twenty-eight outpatients were given psychological tests for anxiety and depression (Hospital Anxiety and Depression Scale; HADS) and QL The European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire C30 (EORTC QLQ-C30) on the same occasion. The association between the patients' emotional function (EF) scoring on EORTC QLQ-C30 and their HADS scores was analyzed by multiple linear regression. RESULTS: Statistically significant negative relationships were found between EF and HADS-A (anxiety), HADS-D (depression), and HADS-T (total score), respectively, with the highest correlation coefficient being for HADS-A. However, HADS-D was significantly more highly correlated than HADS-A to other QL dimensions, and depression was more highly correlated than anxiety with reduced QL. CONCLUSION: The EF dimension of the EORTC QLQ-C30 predominantly assesses anxiety. Depression has a stronger impact on the global QL of patients than anxiety; therefore, the use of an additional instrument is recommended for the assessment of depression in outpatients with colorectal cancer.

Aged↗
PubMed2003

Community-based estimates of incidence and risk factors for childhood pneumonia in Western Sydney.

The aim was to estimate the community incidence and risk factors for all-cause pneumonia in children in Western Sydney, Australia. A cross-sectional randomized computer-assisted telephone interview was conducted in July 2000, in Western Sydney. Parents of 2020 children aged between 5 and 14 years were interviewed about their child's respiratory health since birth. No verification of reported diagnosis was available. Logistic regression analysis was used to determine risk factors for pneumonia. A lifetime diagnosis of pneumonia was reported in 137/2020 (68%) children, giving an estimated incidence in the study sample of 7.6/1000 person-years. Radiological confirmation was reported in 85% (117/137). Hospitalization was reported in 41% (56/137) and antibiotic therapy in 93% (127/137) of cases. Using logistic regression modelling, statistically significant associations with pneumonia were a reported history of either asthma, bronchitis or other lung problems and health problems affecting other systems. In most cases, the diagnosis of asthma preceded the diagnosis of pneumonia. The community incidence of all causes of pneumonia is not well enumerated, either in adults or in children. This study provides community-based incidence data. The incidence of hospitalization for pneumonia in this study is comparable to estimates from studies in comparable populations, suggesting that retrospective parental report for memorable events is likely to be valid. We found a relationship between pneumonia and childhood respiratory diseases such as asthma, which has implications for targeted vaccination strategies.

Adolescent↗
PubMed1992

Population pharmacokinetics of gentamicin in neonates using a nonlinear, mixed-effects model.

The population pharmacokinetics of gentamicin in neonates was determined using a nonlinear, mixed-effects model (NONMEM). The final regression equations derived to estimate clearance (Cl) and volume of distribution (Vd) were Cl = 0.120 * (WT/2.4)1.36 L/hr and Vd = 0.429 * (WT) L. The interindividual variability (% CV) for clearance was 26.2% and for volume of distribution 15.9%. Intraindividual variability was 11.0%. In a separate group of 30 neonates, the predictive ability of the NONMEM-generated population variables was compared to the predictions from a standard two-stage population analysis. The trough concentrations predicted using NONMEM-generated parameters were significantly less biased and more precise; there were no significant differences between the methods in predicting peaks. NONMEM is a useful tool for determining population pharmacokinetics and appears to be consistent across populations using routine clinical data and limited observation.

Gentamicins↗
PubMed1998

Between- and within-cluster covariate effects in the analysis of clustered data.

Standard methods for the regression analysis of clustered data postulate models relating covariates to the response without regard to between- and within-cluster covariate effects. Implicit in these analyses is the assumption that these effects are identical. Example data show that this is frequently not the case and that analyses that ignore differential between- and within-cluster covariate effects can be misleading. Consideration of between- and within-cluster effects also helps to explain observed and theoretical differences between mixture model analyses and those based on conditional likelihood methods. In particular, we show that conditional likelihood methods estimate purely within-cluster covariate effects, whereas mixture model approaches estimate a weighted average of between- and within-cluster covariate effects.

Adolescent↗
PubMed2006

Structured additive regression for categorical space-time data: a mixed model approach.

Motivated by a space-time study on forest health with damage state of trees as the response, we propose a general class of structured additive regression models for categorical responses, allowing for a flexible semiparametric predictor. Nonlinear effects of continuous covariates, time trends, and interactions between continuous covariates are modeled by penalized splines. Spatial effects can be estimated based on Markov random fields, Gaussian random fields, or two-dimensional penalized splines. We present our approach from a Bayesian perspective, with inference based on a categorical linear mixed model representation. The resulting empirical Bayes method is closely related to penalized likelihood estimation in a frequentist setting. Variance components, corresponding to inverse smoothing parameters, are estimated using (approximate) restricted maximum likelihood. In simulation studies we investigate the performance of different choices for the spatial effect, compare the empirical Bayes approach to competing methodology, and study the bias of mixed model estimates. As an application we analyze data from the forest health survey.

Bayes Theorem↗
PubMed1979

Structure-activity relationships in the development of hypoxic cell radiosensitizers. I. Sensitization efficiency.

The efficiency of 35 nitroaromatic and nitroheterocyclic compounds in radiosensitizing hypoxic Chinese Hamster cells in vitro was determined. The concentration C of the compound required to achieve an enhancement ratio of 1.6 was measured, and the redox and partition properties were quantified as the one-electron reduction potential at pH 7, E, and the octanol: water partition coefficient, P, respectively. Most of the compounds studied were 2-nitroimidazoles, but some 4- and 5-nitromidazoles, 5-nitrofurans and nitrobenzenes were investigated for comparison. Together with data for nine nitroimidazoles previously reported, the results were fitted to a structure-activity relationship of the form -log C = b0 + b1E + b2 log P + b3 (log P)2 using multiple linear regression analysis. Statistical tests showed that the coefficients b2 and b3 were not significantly different from zero and the simpler equation, obtained by omitting the terms in log P, explained 85 per cent of the variance in log C. Earlier reports that the radiosensitization efficiency of nitro compounds in vitro largely depends on the reduction potential were confirmed. The conclusive demonstration that P is unimportant in vitro is valuable in interpreting the results of experiments in vivo, where P is expected to have a much greater influence on biological response.

Animals↗
PubMedDate not supplied

A comparison of the fertility of Dominican, Puerto Rican and mainland Puerto Rican adolescents.

Data from three fertility surveys are used to examined the probabilities and determinants of adolescent births among Dominican and Puerto Rican women. Young women in the Dominican Republic are the most likely to have had a child by each year of age from 14 through 24, followed by young women on the Island of Puerto Rico; the probability of an early birth is lowest for Puerto Rican women on the U.S. mainland. Eighteen percent of Dominican women have had a child before their 18th birthday, compared with 13% of women living in Puerto Rico, and 10% of Puerto Rican women in metropolitan New York. The cumulative probabilities that Puerto Rican women will have borne a child before their 20th birthday are almost identical, whether the women live on the island or the U.S. mainland, but the difference between Puerto Rican and Dominican women widens. The order is reversed, however, in the analysis of premarital births: The probability of a premarital birth during adolescence is highest for Puerto Rican women in New York, and lowest for Dominican women. In a separate logistic regression analysis, education and age at first sexual intercourse are shown to be important determinants of adolescent fertility in all three populations.

Adolescent↗
PubMed1993

Women and AIDS: social determinants of sex-related activities.

Female sexual partners of injection drug users are at risk for AIDS because of their association with street drug cultures and all their concomitant risks, including their own non-injecting drug use. This study examines a model of the social determinants of HIV-associated sexual risk behaviors. Multiple linear regression analysis was used to analyze the data for 207 female sexual partners who had never injected drugs. The findings show that crack cocaine use is the strongest contributor to the model, which explains fourteen percent of the variance of sexual risk behavior. The findings suggest that the risks associated with sexual practices are much greater for crack cocaine users than among non users of crack.

Acquired Immunodeficiency Syndrome↗
PubMed1999

An estimation method for the semiparametric mixed effects model.

A semiparametric mixed effects regression model is proposed for the analysis of clustered or longitudinal data with continuous, ordinal, or binary outcome. The common assumption of Gaussian random effects is relaxed by using a predictive recursion method (Newton and Zhang, 1999) to provide a nonparametric smooth density estimate. A new strategy is introduced to accelerate the algorithm. Parameter estimates are obtained by maximizing the marginal profile likelihood by Powell's conjugate direction search method. Monte Carlo results are presented to show that the method can improve the mean squared error of the fixed effects estimators when the random effects distribution is not Gaussian. The usefulness of visualizing the random effects density itself is illustrated in the analysis of data from the Wisconsin Sleep Survey. The proposed estimation procedure is computationally feasible for quite large data sets.

Biometry↗